Efficient Prediction of Chronic Kidney Disease (CKD) Using Artificial Neural Network
Abstract
Chronic kidney
disease (CKD) is a leading cause of mortality around the world. Providing
diagnostic aid for CKD disease by using a set of data that contains only
medical information obtained without advanced medical equipment can help people
who want to discover the disease or the risk of disease at an early stage. The
aim of our project is to classify chronic kidney disease (CKD) by developing a
system using machine learning. Our method is implemented by classification
approach using artificial neural network (ANN), Keras python Library for
sequential model creation. The model used is feed forward network with back
propagation algorithm. The system can assist medical practitioners in the
already existing diagnosis systems. It can also help the patients to know
earlier if they are having CKD or likely to have by using certain attributes.
Country : India
1 Gopaji Monica
Assistant Professor, Department of Computer Science And Engineering, Malla Reddy College of Engineering for Women, Hyderabad -500100, Telangana, India
Koushal Kumar, Abhishek et
al.“Artificial Neural Networks for Diagnosis of Kidney Stones Disease “2012[3]
Berina Alic et al. “Machine Learning Techniques for Classification of Diabetes
and Cardiovascular Diseases” 2015.
